X-ray CT scanner capable of performing improved log conversion

X-ray or gamma ray systems or devices – Specific application – Computerized tomography

Reexamination Certificate

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Details

C378S901000, C378S019000

Reexamination Certificate

active

06829324

ABSTRACT:

BACKGROUND OF THE INVENTION
1. Technical Field of the Invention
The present invention relates to an X-ray computed tomography scanner in which low-count data, which is acquired when an X-ray passes through object's regions whose X-ray absorption coefficients are relatively higher, is effectively used for CT image reconstruction.
2. Description of Related Art
As is well known, X-ray computed tomography (CT) is an imaging technique of producing density images based on X-ray absorption coefficients. An X-ray is radiated toward an object along various radiation angles to scan a section of the object so that resultant X-ray transmission amounts are measured, and X-ray absorption coefficients at each position in the object's section are computed. Using the coefficients, density images are produced. From a different viewpoint, it can be said that the X-ray CT makes use of the fact that the living body is composed of various tissues different in their X-ray absorption coefficients.
In performing the X-ray CT imaging, some regions in a scanned object's section, such as bones, provide higher X-ray absorption coefficients. Such regions are also subjected to X-ray measurement, but amounts of X-ray from the regions, which are detected by an X-ray detector, are extremely low, thereby frequently causing a considerable amount of reduction in the SNR.
An X-ray decays in strength exponentially while traveling through an object. An X-ray detector detects incoming X-rays and outputs signals in proportion to their transmission amounts. The output signals from the detector enter a data acquisition system (DAS), wherein the signal is amplified by amplifiers concurrently with being converted to digital signals by A/D converters.
To obtain projection data composed of a total sum of X-ray absorption coefficients computed along each X-ray path, it is required that the digitized output signals undergo processing called “log conversion” carried as part of the pre-processing for the output signal.
However, the output signals have already contained noise components at the stage of the log conversion. Such noise components include random noise attributable to the detector and DAS.
The random noise is normally negligible, differently from photon noise (serious noise caused by fluctuations in the number of incoming X-ray quantum particles). However, it is not always light to neglect the random noise. Particularly, in cases where, under particular conditions, such as scanning of thinner slices or scanning under lower X-ray amounts, X-rays that have been transmitted through paths of which X-ray absorption is large are detected by a detector, the random noise at the detector is often larger in strength than the photon noise. In such a case, the random noise becomes a dominant in the noise of the output from the detector. Even when no random noise is originated from the detector and DAS, if an amount of incoming X-rays is remarkably low, the amplitude of noise included in the output signal from the detector reaches an unnegligible level, compared to an average level of the output signal.
In the present application, regardless of whether the primary cause is photon noise or noise from the detector and DAS, the signal that contains noise of an unnegligible level compared to an average level of the signal is called “low-count data.”
When reconstructing images with the use of acquired data that contains such low-count data in the conventional manner, many streak artifacts (hereafter referred to as “low-count artifacts”) appear along path directions passing a region where X-ray absorption is larger. The low-count artifacts make it difficult to use such images for diagnosis.
The study about the low-count artifacts, which was conducted by the present inventors, showed that the foregoing log conversion has the nature of amplifying the noise contained in the low-count data. In other words, the conventional log conversion will deteriorate the originally-lower S/N of the low-count data, thereby accelerating the appearance of the local-count artifacts on images.
SUMMARY OF THE INVENTION
The present invention has been made in consideration of the foregoing conventional problems, and an object of the present invention is to eliminates or suppress the low-count artifacts.
In order to realize the foregoing object, as one aspect of the present invention, there is provided an X-ray CT scanner comprising: an X-ray source generating an X-ray; a detector detecting the X-ray generated by the X-ray source and transmitted through an object; a processor producing projection data by applying to an output signal from the detector logarithm conversion processing on a function deviating from an ideal logarithm function; and a reconstruction unit configured to reconstruct an image using the projection data produced by the processor.
An X-ray CT scanner according to the present invention will not stick to the conventional log conversion in producing projection data. The inventors' study into the log conversion revealed that an improved log conversion with the use of a function made to deviate positively in a certain manner from the ideal logarithm function is highly effective for “low-count data” acquired by the detector. It is therefore to eliminate or suppress low-count artifacts from or on reconstructed CT images.
Preferably, the ideal logarithm function is a logarithm function defined by a mathematical formula of y=K·log[b, x] (wherein a variable x is an input, a variable y is an output, and a reference K shows a scaling constant), wherein the function deviating from the ideal logarithm function is configured to have an input/output characteristic deviating from an input/output characteristic defined by the ideal logarithm function.
Still preferably, the function deviating from the ideal logarithm function consists of a function range assigned to the inputs equal to or larger than a specified value and defined by the ideal logarithm function, and a further function range assigned to the inputs less than the specified value and formed to have the deviating input/output characteristic. By way of example, the function range and the further function range are defined individually and separated at a threshold given to the inputs.
It is also preferred that the function deviating from the ideal logarithm function is defined as a function providing one curve consisting of both of the function range and the further function range. For example, the processor includes a table where input/output data of the one curve are stored and reference means configured to perform the logarithm conversion processing with reference to the input/output data stored in the table.
It is also preferred that the processor has weighting means configured to perform the logarithm conversion processing by performing weighted summation of plural log conversion results.
Still it is preferred that the further function range is smaller in an angle of the input/output characteristic than the function range.


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